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Parameterised Complexity of Abduction in Schaefer's Framework

机译:舍费尔框架中绑架的参数化复杂性

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Abductive reasoning is a non-monotonic formalism stemming from the work of Peirce. It describes the process of deriving the most plausible explanations of known facts. Considering the positive version asking for sets of variables as explanations, we study, besides asking for existence of the set of explanations, two explanation size limited variants of this reasoning problem (less than or equal to, and equal to). In this paper, we present a thorough two-dimensional classification of these problems. The first dimension is regarding the parameterised complexity under a wealth of different parameterisations. The second dimension spans through all possible Boolean fragments of these problems in Schaefer's constraint satisfaction framework with co-clones (STOC 1978). Thereby, we almost complete the parameterised picture started by Fellows et al. (AAAI 2012), partially building on results of Nordh and Zanuttini (Artif. Intell. 2008). In this process, we outline a fine-grained analysis of the inherent parameterised intractability of these problems and pinpoint their FPT parts. As the standard algebraic approach is not applicable to our problems, we develop an alternative method that makes the algebraic tools partially available again.
机译:归纳推理是源自皮尔斯的工作的非单调形式主义。它描述了对已知事实进行最合理解释的过程。考虑到要求变量集作为解释的肯定版本,我们除了要求存在解释集外,还研究此推理问题的两个解释大小受限的变体(小于或等于和等于)。在本文中,我们对这些问题进行了全面的二维分类。第一维是关于大量不同参数设置下的参数设置复杂性。第二个维度跨越了Schaefer的带有共克隆的约束满足框架中这些问题的所有可能的布尔片段(STOC 1978)。因此,我们几乎完成了由Fellows等人开始的参数化图片。 (AAAI 2012),部分基于Nordh和Zanuttini(Artif。Intell。2008)的结果。在此过程中,我们概述了这些问题的固有参数化难处理性的细粒度分析,并指出了它们的FPT部分。由于标准代数方法不适用于我们的问题,因此我们开发了另一种方法,使代数工具再次部分可用。

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